摘要
大气加权平均温度(Tm)是全球导航卫星系统(GNSS)技术反演大气水汽的关键因素,针对已有区域Tm模型未能同时顾及Tm在垂直方向的非线性变化和精细的日变化以及在构建模型时仅使用单一格网点数据等问题,本文以中国地区为研究区域,提出了一种基于滑动窗口的区域Tm建模方法,利用2012—2017年欧洲中期天气预报中心(ECMWF)的ERA5资料建立顾及日变化和非线性垂直改正的区域Tm格网模型(CNTm模型).联合未参与建模的2018年ERA5资料和无线电探空数据,验证CNTm模型的精度和适用性,并与当前广泛使用的GPT3模型和顾及了线性垂直改正的IGPT2w模型进行精度对比.结果表明:以2018年ERA5资料和无线电探空数据为参考值,CNTm模型的均方根误差(RMS)分别为3.31 K和3.21 K,其精度相较于GPT3模型分别提高了约16%和23%,相较于IGPT2w模型分别提高了约7%和11%;顾及了非线性垂直改正的CNTm模型的估计值更接近于Tm在垂直方向上的变化趋势,且CNTm模型能够捕获Tm的日变化.由于CNTm模型在研究区域表现出优异的性能,因此,其在研究区域实时高精度、高分辨率GNSS水汽监测中具有重要的应用.
Atmospheric weighted mean temperature(Tm)is a key factor of Global Navigation Satellite System(GNSS)to retrieve atmospheric water vapor.In response to the problems of existing regional models not being able to simultaneously consider nonlinear changes in the vertical direction and fine diurnal variations,as well as using only a single grid point data when constructing the model,this paper takes China as the research area and proposes a sliding window based regional modeling method.The Tm grid model(CNTm model)that considering diurnal variations and nonlinear vertical corrections is developed using ERA5 data from the European Centre for Medium Range Weather Forecasts(ECMWF)in 2012 to 2017.Both ERA5 data and radiosonde data that were not involved in the modeling in 2018 are treated as reference values to assess the accuracy and applicability of CNTm model,GPT3 model and IGPT2w model are also used to compared with CNTm model.The results show that based on ERA5 data and radiosonde data in 2018,the root mean square error(RMS)of CNTm model are 3.31 K and 3.21 K,respectively.Compared with GPT3 model,the accuracy of CNTm model is improved by 16%and 23%,and compared with IGPT2w model,the accuracy is improved by 7%and 11%,respectively;The estimated value of CNTm model that considering nonlinear vertical correction is close to the vertical trend of Tm,and CNTm model can provide the diurnal variation of Tm.Because CNTm model shows excellent performance in the study area,it has an important application in real-time high-precision and high-resolution GNSS water vapor monitoring in the study area.
作者
黄良珂
廖发圣
陈发德
张红星
黎峻宇
黄玲
刘立龙
HUANG LiangKe;LIAO FaSheng;CHEN FaDe;ZHANG HongXing;LI JunYu;HUANG Ling;LIU LiLong(College of Geomatics and Geoinformation,Guilin University of Technology,Guilin 541004,China;Innovation Academy for Precision Measurement Science and Technology,Chinese Academy of Sciences,Wuhan 430071,China)
出处
《地球物理学报》
SCIE
EI
CAS
CSCD
北大核心
2024年第5期1721-1732,共12页
Chinese Journal of Geophysics
基金
国家自然科学基金(41864002)
广西自然科学基金(2023GXNSFAA026434)
广西“八桂学者”岗位专项
广西研究生教育创新计划项目(YCSW2022322)联合资助.
